E-Map: A Visual Analytics Approach for Exploring Significant Event Evolutions in Social Media

Chen, S; Lin, L; Yuan, X; Liang, J; Zhang, X

E-Map: A Visual Analytics Approach for Exploring Significant Event Evolutions in Social Media

Chen, S Lin, L Yuan, X Liang, J

Zhang, X

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Publication Type:: Conference Proceeding
Citation:: 2017 IEEE Conference on Visual Analytics Science and Technology, VAST 2017 - Proceedings, 2018, pp. 36 - 47
Issue Date:: 2018-12-21

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Field	Value	Language
dc.contributor.author	Chen, S	en_US
dc.contributor.author	Lin, L	en_US
dc.contributor.author	Yuan, X	en_US
dc.contributor.author	Liang, J https://orcid.org/0000-0001-7179-5208	en_US
dc.contributor.author	Zhang, X	en_US
dc.date.issued	2018-12-21	en_US
dc.identifier.citation	2017 IEEE Conference on Visual Analytics Science and Technology, VAST 2017 - Proceedings, 2018, pp. 36 - 47	en_US
dc.identifier.isbn	9781538631638	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126554
dc.description.abstract	© 2017 IEEE. Significant events are often discussed and spread through social media, involving many people. Reposting activities and opinions expressed in social media offer good opportunities to understand the evolution of events. However, the dynamics of reposting activities and the diversity of user comments pose challenges to understand event-related social media data. We propose E-Map, a visual analytics approach that uses map-like visualization tools to help multi-faceted analysis of social media data on a significant event and in-depth understanding of the development of the event. E-Map transforms extracted keywords, messages, and reposting behaviors into map features such as cities, towns, and rivers to build a structured and semantic space for users to explore. It also visualizes complex posting and reposting behaviors as simple trajectories and connections that can be easily followed. By supporting multi-level spatial temporal exploration, E-Map helps to reveal the patterns of event development and key players in an event, disclosing the ways they shape and affect the development of the event. Two cases analysing real-world events confirm the capacities of E-Map in facilitating the analysis of event evolution with social media data.	en_US
dc.relation.ispartof	2017 IEEE Conference on Visual Analytics Science and Technology, VAST 2017 - Proceedings	en_US
dc.relation.isbasedon	10.1109/VAST.2017.8585638	en_US
dc.title	E-Map: A Visual Analytics Approach for Exploring Significant Event Evolutions in Social Media	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2017 IEEE. Significant events are often discussed and spread through social media, involving many people. Reposting activities and opinions expressed in social media offer good opportunities to understand the evolution of events. However, the dynamics of reposting activities and the diversity of user comments pose challenges to understand event-related social media data. We propose E-Map, a visual analytics approach that uses map-like visualization tools to help multi-faceted analysis of social media data on a significant event and in-depth understanding of the development of the event. E-Map transforms extracted keywords, messages, and reposting behaviors into map features such as cities, towns, and rivers to build a structured and semantic space for users to explore. It also visualizes complex posting and reposting behaviors as simple trajectories and connections that can be easily followed. By supporting multi-level spatial temporal exploration, E-Map helps to reveal the patterns of event development and key players in an event, disclosing the ways they shape and affect the development of the event. Two cases analysing real-world events confirm the capacities of E-Map in facilitating the analysis of event evolution with social media data.

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http://hdl.handle.net/10453/126554